DocumentCode
1799015
Title
Video transcoding time prediction for proactive load balancing
Author
Deneke, T. ; Haile, Habtegebreil ; Lafond, S. ; Lilius, Johan
Author_Institution
Abo Akad. Univ., Abo, Finland
fYear
2014
fDate
14-18 July 2014
Firstpage
1
Lastpage
6
Abstract
In this paper, we present a method for predicting the transcoding time of videos given an input video stream and its transcoding parameters. Video transcoding time is treated as a random variable and is statistically predicted from past observations. Our proposed method predicts the transcoding time as a function of several parameters of the input and output video streams, and does not require any detailed information about the codec used. We show the effectiveness of our method via comparing the resulting predictions with the actual transcoding times on unseen video streams. Simulation results show that our prediction method enables a significantly better load balancing of transcoding jobs than classical load balancing methods.
Keywords
prediction theory; resource allocation; transcoding; video coding; video streaming; input video stream; proactive load balancing; video transcoding time prediction; Bit rate; Codecs; Load management; Load modeling; Predictive models; Transcoding; YouTube; Load Balancing; Machine Learning; Prediction; Transcoding;
fLanguage
English
Publisher
ieee
Conference_Titel
Multimedia and Expo (ICME), 2014 IEEE International Conference on
Conference_Location
Chengdu
Type
conf
DOI
10.1109/ICME.2014.6890256
Filename
6890256
Link To Document